The discovery and development of RNAi and CRISPR/Cas9 genetic screening technologies have provided researchers with invaluable tools for wide-scale and rapid genetic screening. A central goal of our research program has been to develop methodology for efficient application of these screening technologies in hematopoietic cell lineages, and to implement screens in both human and mouse hematopoietic cells to interrogate the mechanistic basis of immune cell responses to pathogenic stimuli. Our current efforts are focused on macrophages as they form the first line of defense against numerous bacterial and viral pathogens and characterization of these initial encounters are central to the LSB-wide efforts to generate quantitative models of host-pathogen interactions. We have generated reporter cell lines for mouse and human macrophages that provide a comprehensive range of biosensors for evaluation of the macrophage activation profile in response to various pathogenic inputs. We have also developed robust siRNA delivery protocols that avoid non-specific activation of the macrophage response to dsRNA and we have confirmed our assays conform to the reproducibility and uniformity criteria established in the NCATS high throughput screening best practices guidelines. This year, we described the utility of these macrophage cell systems for siRNA screening of pathogen responses and showed that our approach to reporter cell development and siRNA delivery optimization provides an experimental paradigm with significant potential for developing genetic screening platforms in mammalian cells (Li et al (2015) Sci. Rep. 5:9559). Using the platforms described above, this year we also completed a comprehensive screening analysis of the canonical TLR signaling components in human and mouse macrophages. This 126-gene set included TLR receptors, proximal signaling components, NF-&#954;B and MAPK pathway proteins, transcription factors, cytokines and negative regulators. We targeted this canonical TLR gene set with six different individual siRNAs for every gene, which significantly reduces the occurrence of off-target effects. We screened both human and mouse macrophages with multiple TLR ligands to compare the pathway component usage in response to varied stimuli. While confirming the expected specificity for the TLRs and some of the core pathway components, this study has identify some unexpected selectivity in signaling responses through different TLR pathways, and also some particularly striking differences between human and mouse macrophages. Mouse cells are more sensitive than human cells to depletion of CD14, IRAK4, IRAK2, PI3K signaling, IKK&#946; and MEK1 and 2, while human cells are more sensitive to depletion of IRAK1, TRAF6, the TAK1/TAB complex and Tpl2 among others. Among the gene-specific phenotypes, we have further investigated differences in IRAK protein usage. Importantly, we confirmed that the screen phenotypes seen using our macrophage reporter cell lines were also observed in primary cells. We found that mouse bone marrow derived macrophages (BMDM) are highly sensitive to depletion of IRAK4 or IRAK2, but show little perturbation of TLR responses with depletion of IRAK1. In contrast, primary human blood-derived macrophages are highly sensitive to IRAK1 depletion for signaling, transcription and secretion responses to TLR ligands, but are more resistant to IRAK4 and IRAK2 depletion. In further analyses we find that there are both quantitative and qualitative differences in how human and mouse macrophages employ the IRAK proteins for TLR signaling. Our study identifies a previously unappreciated critical role for IRAK1 in TLR signaling in human macrophages, which could potentially shed new light on the association of IRAK1 with several autoimmune diseases. A manuscript describing the above screen is currently under review. RNAi screen data are susceptible to a myriad of experimental biases, some of which can be mitigated by computational analysis. During the analysis of the primary and secondary screen data from our genome-wide screens, we sought to improve the integration of the screen analysis process. This year, in collaboration with Bhaskar Dutta in the LSB bioinformatics support team, we have developed a user-friendly platform for integrated analysis and visualization of RNAi screen data, named Comprehensive Analysis of RNAi Data (CARD). This unique application allows users to apply all of the major steps involved in analysis of RNAi screening data within a single framework and through a user-friendly web interface (https://card.niaid.nih.gov). CARD not only implements many existing algorithms, but also improves them where appropriate and incorporates novel functionalities, and the intuitive web-interface of CARD enables users without programming experience to run and monitor the progress of multiple sophisticated algorithms from an interactive dashboard. As the screen results and their interpretation are dependent on factors like biological system, assay type, experimental conditions, etc., CARD provides flexibility to users to conveniently customize the analysis parameters. CARD also uses cutting-edge data visualization techniques that allow users to interact dynamically with the figures and tables on the web-browser to facilitate the hit selection process. We have applied CARD to several published screen datasets and demonstrated both increased hit validation rates and improved hit gene overlap between related screens. A manuscript describing the development and application of the CARD software to RNAi screen data is currently under review, and numerous other screening groups are incorporating CARD into their data analysis workflow. We are also now implementing CARD to gain more detailed insight to the similarities and differences in the LPS response network of mouse and human macrophages from our genome-wide siRNA screens. The signaling pathways and transcription factor responses induced in macrophages upon TLR stimulation are regulated by feedback loops that modulate the kinetics and magnitude of gene transcription. Among these, NF-&#954;B has been a paradigm for a signal- responsive transcription factor that operates in a feedback regulatory network. Despite the considerable literature on NF-&#954;B activation and function, there remains a lack of data on NF-&#954;B single cell dynamics in hematopoietic cells (especially macrophages) responding to pathogenic stimuli. We have previously described the use of our screening reporter cells, developed with dual assay readouts for NF-&#954;B and TNF-&#945; transcription, to identify a novel positive feedback loop in the macrophage NF-&#954;B activation process which supports a robust inflammatory program at higher TLR ligand doses. Using genome-wide siRNA screen data, we discovered an important role for the transcription factor Ikaros in supporting this inflammatory response (Sung et al (2014) Sci Signal, 7: p. ra6). This year we have investigated the role of Ikaros in the broader LPS-induced gene program. In primary macrophages from Ikaros KO mice, we find using RNA-seq that over 50% of LPS induced genes are attenuated, and using DNase-seq, we find that the chromatin accessibility changes induced by LPS are lost in the absence of Ikaros. ChIP-seq analysis shows that sustained NF-&#954;B occupied sites, which are co-occupied by Ikaros in WT cells, are lost in KO cells. Together, these data suggest a major role for Ikaros in sustaining the inflammatory gene program in LPS stimulated macrophages.